1. Critical brain dynamics are increasingly recognized to be important in cortex function. We have expanded on our previous finding of fluctuation analysis as a marker for critical dynamics in neuronal systems. Taking advantage of a data base in Freiburg, Germany on long-term recordings from humans suffering from epilepsy, fluctuation analysis was used to study the effect of anti-epileptic drugs (AED). This work is of high clinical relevance as it demonstrates successfully how to non-invasively measure the excitability of cortex in humans and to quantify the change in fluctuations in response to AEDs (Meisel et al., 2015). Intrinsic excitability measures track antiepileptic drug action and uncover increasing/decreasing excitability over the wake/sleep cycle. Pathological changes in excitability of cortical tissue commonly underlie the initiation and spread of seizure activity in patients suffering from epilepsy. Accordingly, monitoring excitability and controlling its degree using antiepileptic drugs (AEDs) is of prime importance for clinical care and treatment. To date, adequate measures of excitability and action of AEDs have been difficult to identify. Recent insights into ongoing cortical activity have identified global levels of phase synchronization as measures that characterize normal levels of excitability and quantify any deviation therefrom. Here, we explore the usefulness of these intrinsic measures to quantify cortical excitability in humans. First, we observe a correlation of such markers with stimulation-evoked responses suggesting them to be viable excitability measures based on ongoing activity. Second, we report a significant covariation with the level of AED load and a wake-dependent modulation. Our results indicate that excitability in epileptic networks is effectively reduced by AEDs and suggest the proposed markers as useful candidates to quantify excitability in routine clinical conditions overcoming the limitations of electrical or magnetic stimulation. The wake-dependent time course of these metrics suggests a homeostatic role of sleep, to rebalance cortical excitability. 2. Numerous efforts in my laboratory focus on the development of novel methods or expansion of existing methods to study neuronal population activity at many different scales. By combining intracellular calcium imaging in neuronal cell cultures with diffusion functional magnetic resonance imaging (diffusion fMRI) we were able to accurately identify pathological and non-pathological conditions to monitor neuronal activity using MRI. This work established a novel test bed to develop diffusion MRI for measuring neuronal population activity (Bai et al, 2015, 2016). Assessing the sensitivity of diffusion MRI to detect neuronal activity directly. Functional MRI (fMRI) is widely used to study brain function in the neurosciences. Unfortunately, conventional fMRI only indirectly assesses neuronal activity via hemodynamic coupling. Diffusion fMRI was proposed as a more direct and accurate fMRI method to detect neuronal activity, yet confirmative findings have proven difficult to obtain. Given that the underlying relation between tissue water diffusion changes and neuronal activity remains unclear, the rationale for using diffusion MRI to monitor neuronal activity has yet to be clearly established. Here, we studied the correlation between water diffusion and neuronal activity in vitro by simultaneous calcium fluorescence imaging and diffusion MR acquisition. We used organotypic cortical cultures from rat brains as a biological model system, in which spontaneous neuronal activity robustly emerges free of hemodynamic and other artifacts. Simultaneous fluorescent calcium images of neuronal activity are then directly correlated with diffusion MR signals now free of confounds typically encountered in vivo. Although a simultaneous increase of diffusion-weighted MR signals was observed together with the prolonged depolarization of neurons induced by pharmacological manipulations (in which cell swelling was demonstrated to play an important role), no evidence was found that diffusion MR signals directly correlate with normal spontaneous neuronal activity. These results suggest that, whereas current diffusion MR methods could monitor pathological conditions such as hyperexcitability, e.g., those seen in epilepsy, they do not appear to be sensitive or specific enough to detect or follow normal neuronal activity. 3. Critical systems that exhibit neuronal avalanches surprise through their richness in temporal outbursts. The temporal dependencies of neuronal avalanches can similarly like in earthquake reveal complex historical dependencies that open new avenues for temporal coding. This was for the first time deeper explored in collaboration with European physicists who are experts in earthquake time series analysis in our 2014 paper. We have now expanded on this work identifying clear relationships between avalanche sizes and quiet times, the time between successive avalanches (Lombardi et al. 2016). Temporal correlations in neuronal avalanche occurrence. Ongoing cortical activity consists of sequences of synchronized bursts, named neuronal avalanches, whose size and duration are power law distributed. These features have been observed in a variety of systems and conditions, at all spatial scales, supporting scale invariance, universality and therefore criticality. However, the mechanisms leading to burst triggering, as well as the relationship between bursts and quiescence, are still unclear. The analysis of temporal correlations constitutes a major step towards a deeper understanding of burst dynamics. Here, we investigate the relation between avalanche sizes and quiet times, as well as between sizes of consecutive avalanches recorded in cortex slice cultures. We show that quiet times depend on the size of preceding avalanches and, at the same time, influence the size of the following one. Moreover we evidence that sizes of consecutive avalanches are correlated. In particular, we show that an avalanche tends to be larger or smaller than the following one for short or long time separation, respectively. Our analysis represents the first attempt to provide a quantitative estimate of correlations between activity and quiescence in the framework of neuronal avalanches and will help to enlighten the mechanisms underlying spontaneous activity.